Modeling cultural evolution Language acquisition as multiple-cue integration
نویسنده
چکیده
Computational and mathematical modeling has revealed that cultural evolution may have played a key role in the evolution of language. In this chapter, I explore the hypothesis that processes of cultural transmission have to a large extent shaped language to !t domain-general constraints deriving from the human brain. An implication of this view is that much of the neural hardware involved in language is not speci!c to it. But how could language have evolved to be as complex as it is without language-speci!c constraints? Based on computational modeling of the cultural evolution of language, I propose that language has evolved to rely on a multitude of probabilistic information sources for its acquisition, allowing it to be as expressive as possible while still being learnable by domain-general learning mechanisms. Empirical predictions are derived from this perspective regarding the role of phonological cues in the learning of basic aspects of syntax. "ese predictions are corroborated by results from corpus analyses, computational modeling, and human experimentation, suggesting that the integration of phonological cues with other types of information is integral to the computational architecture of our language capacity. I conclude by considering how computational modeling of cultural evolution can help us understand the evolution of language.
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Language Has Evolved to Depend on Multiple-Cue Integration
Recent research on language evolution suggests that language to a large extent has been shaped by cultural evolution to fit domain-general constraints deriving from the human brain. An implication of this view is that much of the neural hardware involved in language is not specific to it. This means that language has to be acquired largely by mechanisms that are not uniquely dedicated for this ...
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تاریخ انتشار 2012